Download or read book Subphonetic Acoustic Modeling for Speaker independent Continuous Speech Recognition written by Mei-Yuh Hwang and published by . This book was released on 1993 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Subphonetic Acoustic Modeling for Speaker independent Continuous Speech Recognition written by and published by . This book was released on 1993 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: To model the acoustics of a large vocabulary well while staying within a reasonable memory capacity, most speech recognition systems use phonetic models to share parameters across different words in the vocabulary. This dissertation investigates the merits of modeling at the subphonetic level. We demonstrate that sharing parameters at the subphonetic level provides more accurate acoustic models than sharing at the phonetic level. The concept of subphonetic parameter sharing can be applied to any class of parametric models. Since the first-order hidden Markov model (HMM) has been overwhelmingly successful in speech recognition, this dissertation bases all its studies and experiments on HMMs. The subphonetic unit we investigate is the state of phonetic HMMs. We develop a system in which similar Markov states of phonetic models share the same Markov parameters. The shared parameter (i.e., the output distribution) associated with a cluster of similar states is called a senone because of its state dependency. The phonetic models that share senones are shared-distribution models or SDMs. Experiments show that SDMs offer more accurate acoustic models than the generalized-triphone model presented by Lee. Senones are next applied to offer accurate models for triphones not experienced in the system training data. In this dissertation, two approaches for modeling unseen triphones are studied - purely decision-tree based senones and a hybrid approach using the concept of Markov state quantization. Both approaches indeed offer a significant error reduction over the previously accepted approach of monophone model substitution. However, the purely decision-tree based senone approach is preferred for its simplicity.
Download or read book Automatic Speech and Speaker Recognition written by Chin-Hui Lee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in the field of automatic speech and speaker recognition has made a number of significant advances in the last two decades, influenced by advances in signal processing, algorithms, architectures, and hardware. These advances include: the adoption of a statistical pattern recognition paradigm; the use of the hidden Markov modeling framework to characterize both the spectral and the temporal variations in the speech signal; the use of a large set of speech utterance examples from a large population of speakers to train the hidden Markov models of some fundamental speech units; the organization of speech and language knowledge sources into a structural finite state network; and the use of dynamic, programming based heuristic search methods to find the best word sequence in the lexical network corresponding to the spoken utterance. Automatic Speech and Speaker Recognition: Advanced Topics groups together in a single volume a number of important topics on speech and speaker recognition, topics which are of fundamental importance, but not yet covered in detail in existing textbooks. Although no explicit partition is given, the book is divided into five parts: Chapters 1-2 are devoted to technology overviews; Chapters 3-12 discuss acoustic modeling of fundamental speech units and lexical modeling of words and pronunciations; Chapters 13-15 address the issues related to flexibility and robustness; Chapter 16-18 concern the theoretical and practical issues of search; Chapters 19-20 give two examples of algorithm and implementational aspects for recognition system realization. Audience: A reference book for speech researchers and graduate students interested in pursuing potential research on the topic. May also be used as a text for advanced courses on the subject.
Download or read book Speaker Independent Continuous Speech Recognition Using an Acoustic phonetic Itatian Corpus written by B. Angelini and published by . This book was released on 1994 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Segment Based Acoustic Models for Continuous Speech Recognition written by and published by . This book was released on 1994 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition by extending previous work in segment-based modeling and by introducing a new hierarchical approach to representing intra-utterance statistical dependencies. These techniques, which have high computational costs because of the large search space associated with higher order models, are made feasible through rescoring a set of HMM-generated N-best sentence hypotheses. We expect these different modeling, techniques to result in improved recognition performance over that achieved by current systems, which handle only frame-based observations and assume that these observations are independent given an underlying state sequence. In the past quarter, our focus has been on developing the theory and initial implementation behind high level models and search algorithms to accommodate these models.
Download or read book High Order Modeling Techniques for Continuous Speech Recognition written by and published by . This book was released on 1995 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition by developing acoustic and language models aimed at representing high-order statistical dependencies within and across utterances, including speaker, channel and topic characteristics. These techniques, which have high computational costs because of the large search space associated with higher order models, are made feasible through a multi-pass search strategy that involves recording a constrained space given by an HNM decoding. With these overall project goals, the primary research efforts and results over the last quarter have included: (1) an extensive literature survey of research adaptation; (2) development of a trigram word prediction tool for the use in experiments t6 estimate the entropy of conversational English; (3) further experimental exploration of dependence tree topology design and extension of the modeling framework to handle continuous observation vectors; (4) initiated work on HMM topology design; and (5) furthered efforts on establishing a baseline HTK recognition system for a task of recognizing the Marcophone natura numbers data, on which we currently achieve 76% word accuracy.
Download or read book Lexical Modeling in a Speaker Independent Speech Understanding System written by Charles Clayton Wooters and published by . This book was released on 1993 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modern Speech Recognition written by S. Ramakrishnan and published by BoD – Books on Demand. This book was released on 2012-11-28 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses primarily on speech recognition and the related tasks such as speech enhancement and modeling. This book comprises 3 sections and thirteen chapters written by eminent researchers from USA, Brazil, Australia, Saudi Arabia, Japan, Ireland, Taiwan, Mexico, Slovakia and India. Section 1 on speech recognition consists of seven chapters. Sections 2 and 3 on speech enhancement and speech modeling have three chapters each respectively to supplement section 1. We sincerely believe that thorough reading of these thirteen chapters will provide comprehensive knowledge on modern speech recognition approaches to the readers.
Download or read book Automatic Speech and Speaker Recognition written by Joseph Keshet and published by Wiley. This book was released on 2009-04-27 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses large margin and kernel methods for speech and speaker recognition Speech and Speaker Recognition: Large Margin and Kernel Methods is a collation of research in the recent advances in large margin and kernel methods, as applied to the field of speech and speaker recognition. It presents theoretical and practical foundations of these methods, from support vector machines to large margin methods for structured learning. It also provides examples of large margin based acoustic modelling for continuous speech recognizers, where the grounds for practical large margin sequence learning are set. Large margin methods for discriminative language modelling and text independent speaker verification are also addressed in this book. Key Features: Provides an up-to-date snapshot of the current state of research in this field Covers important aspects of extending the binary support vector machine to speech and speaker recognition applications Discusses large margin and kernel method algorithms for sequence prediction required for acoustic modeling Reviews past and present work on discriminative training of language models, and describes different large margin algorithms for the application of part-of-speech tagging Surveys recent work on the use of kernel approaches to text-independent speaker verification, and introduces the main concepts and algorithms Surveys recent work on kernel approaches to learning a similarity matrix from data This book will be of interest to researchers, practitioners, engineers, and scientists in speech processing and machine learning fields.
Download or read book Ensemble Acoustic Modeling in Automatic Speech Recognition written by Xin Chen and published by . This book was released on 2011 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, several new approaches of using data sampling to construct an Ensemble of Acoustic Models (EAM) for speech recognition are proposed. A straightforward method of data sampling is Cross Validation (CV) data partition. In the direction of improving inter-model diversity within an EAM for speaker independent speech recognition, we propose Speaker Clustering (SC) based data sampling. In the direction of improving base model quality as well as inter-model diversity, we further investigate the effects of several successful techniques of single model training in speech recognition on the proposed ensemble acoustic models, including Cross Validation Expectation Maximization (CVEM), Discriminative Training (DT), and Multiple Layer Perceptron (MLP) features. We have evaluated the proposed methods on TIMIT phoneme recognition task as well as on a telemedicine automatic captioning task. The proposed EAMs have led to significant improvements in recognition accuracy over conventional Hidden Markov Model (HMM) baseline systems, and the integration of EAM with CVEM, DT and MLP has also significantly improved the accuracy performances of CVEM, DT, and MLP based single model systems. We further investigated the largely unstudied factor of inter-model diversity, and proposed several methods to explicit measure inter-model diversity. We demonstrate a positive relation between enlarging inter-model diversity and increasing EAM quality. Compacting the acoustic model to a reasonable size for practical applications while maintaining a reasonable performance is needed for EAM. Toward this goal, in this dissertation, we discuss and investigate several distance measures and proposed global optimization algorithms for clustering methods. We also proposed an explicit PDT (EPDT) state tying approach that allows Phoneme data Sharing (PS) for its potential capability in accommodating pronunciation variations.
Download or read book Cross Word Modeling for Arabic Speech Recognition written by Dia AbuZeina and published by Springer Science & Business Media. This book was released on 2011-11-25 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cross-Word Modeling for Arabic Speech Recognition utilizes phonological rules in order to model the cross-word problem, a merging of adjacent words in speech caused by continuous speech, to enhance the performance of continuous speech recognition systems. The author aims to provide an understanding of the cross-word problem and how it can be avoided, specifically focusing on Arabic phonology using an HHM-based classifier.
Download or read book Speech and Speaker Recognition written by Manfred Robert Schroeder and published by Karger Medical and Scientific Publishers. This book was released on 1985-01-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Techniques for Noise Robustness in Automatic Speech Recognition written by Tuomas Virtanen and published by John Wiley & Sons. This book was released on 2012-09-19 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech. Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Includes contributions from top ASR researchers from leading research units in the field
Download or read book Acoustic Modeling for Efficient Speaker Verification written by Bing Xiang and published by . This book was released on 2003 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Broadcast News Workshop 99 Proceedings written by Darpa and published by Morgan Kaufmann. This book was released on 1999-06-29 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonlinear Speech Modeling and Applications written by Gerard Chollet and published by Springer Science & Business Media. This book was released on 2005-07-04 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the revised tutorial lectures given at the International Summer School on Nonlinear Speech Processing-Algorithms and Analysis held in Vietri sul Mare, Salerno, Italy in September 2004. The 14 revised tutorial lectures by leading international researchers are organized in topical sections on dealing with nonlinearities in speech signals, acoustic-to-articulatory modeling of speech phenomena, data driven and speech processing algorithms, and algorithms and models based on speech perception mechanisms. Besides the tutorial lectures, 15 revised reviewed papers are included presenting original research results on task oriented speech applications.
